NDLI: Social collaborative retrieval

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Social collaborative retrieval

Content Provider	ACM Digital Library
Author	Hero, Alfred Hsiao, Ko-Jen Kulesza, Alex
Abstract	Socially-based recommendation systems have recently attracted significant interest, and a number of studies have shown that social information can dramatically improve a system's predictions of user interests. Meanwhile, there are now many potential applications that involve aspects of both recommendation and information retrieval, and the task of collaborative retrieval---a combination of these two traditional problems---has recently been introduced. Successful collaborative retrieval requires overcoming severe data sparsity, making additional sources of information, such as social graphs, particularly valuable. In this paper we propose a new model for collaborative retrieval, and show that our algorithm outperforms current state-of-the-art approaches by incorporating information from social networks. We also provide empirical analyses of the ways in which cultural interests propagate along a social graph using a real-world music dataset.
Starting Page	293
Ending Page	302
Page Count	10
File Format	PDF
ISBN	9781450323512
DOI	10.1145/2556195.2556255
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-02-24
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Collaborative filtering Information retrieval Social networks
Content Type	Text
Resource Type	Article

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